Card Price Prediction of Trading Cards Using Machine Learning Methods

  • Hiroki SakajiEmail author
  • Akio Kobayashi
  • Masaki Kohana
  • Yasunao Takano
  • Kiyoshi Izumi
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1036)


In this paper, we try to predict the card prices of the trading card game using their information. The trading card game market is growing by the increasing popularity of the board game or the digital card game in the e-sports in recent years. The trading card game is a kind of card game which two or more people plays a card with some text or symbols those characteristics expresses a ruling or interaction to the other card. This interaction of cards may work effectively in the game, prices of those card pairs will be increased with the popularity of its combination. We have a hypothesis that card text is useful for prediction of card prices from the importance of card combinations. Therefore, in this research, we focus on not only the basic card information but also card text. Moreover, we use several machine learning method for prediction of card prices, and we analyze which machine learning method is an effect.


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Hiroki Sakaji
    • 1
    Email author
  • Akio Kobayashi
    • 2
  • Masaki Kohana
    • 3
  • Yasunao Takano
    • 4
  • Kiyoshi Izumi
    • 1
  1. 1.The University of TokyoTokyoJapan
  2. 2.RIKEN AIP CenterTokyoJapan
  3. 3.Chuo UniversityTokyoJapan
  4. 4.Kitasato UniversitySagamihara-shiJapan

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